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arXiv AI By Yanan Wu, Yalin Yang, Chengbin Deng

ArchiveLens: A Generative Spatial Knowledge Framework for Semantic Reconstruction of Historical Maps

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ArchiveLens is a generative spatial knowledge framework that transforms historical maps into entity‑centric, machine‑queryable geospatial databases. The pipeline separates morphological and semantic reconstruction into three stages: building footprint extraction with tiled YOLOv11‑seg, deterministic material classification using HSV color thresholds, and localized attribute parsing via a quantized vision‑language model with domain‑specific prompts. Applied to 445 Sanborn map sheets of Chicago (1918‑1950), the system delivers high geometric and semantic accuracy and enables researchers to query building attributes and compare spatial patterns across time.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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